Forecasting the Path of US CO2 Emissions Using State-Level Information

36 Pages Posted: 10 Sep 2013

See all articles by Max Auffhammer

Max Auffhammer

University of California, Berkeley - College of Natural Resources, Department of Agricultural & Resource Economics

Ralf Steinhauser

Universit at Hamburg; Research School of Economics

Date Written: May 29, 2010

Abstract

In this paper we compare the most common reduced form models used for emissions forecasting, point out shortcomings and suggest improvements. Using a U.S. state level panel data set of CO2 emissions we test the performance of existing models against a large universe of potential reduced form models. Our preferred measure of model performance is the squared out-of-sample prediction error of aggregate CO2 emissions. We find that leading models in the literature, as well as models selected based on an emissions per capita loss measure or different in-sample selection criteria, perform significantly worse compared to the best model chosen based directly on the out-of-sample loss measure defined over aggregate emissions. Unlike the existing literature, the tests of model superiority employed here account for model search or ‘data snooping’ involved in identifying a preferred model. Forecasts from our best performing model for the United States are 100 million tons of carbon lower than existing scenarios predict.

Keywords: Forecasting, Climate Change, CO2 Emissions, Data Snooping, Selection Criteria

JEL Classification: Q43, C53

Suggested Citation

Auffhammer, Maximilian and Steinhauser, Ralf, Forecasting the Path of US CO2 Emissions Using State-Level Information (May 29, 2010). Review of Economics and Statistics, Vol. 94, No. 1, 2012. Available at SSRN: https://ssrn.com/abstract=2322841

Maximilian Auffhammer

University of California, Berkeley - College of Natural Resources, Department of Agricultural & Resource Economics ( email )

Berkeley, CA 94720
United States

Ralf Steinhauser (Contact Author)

Universit at Hamburg ( email )

Welckerstr. 8,
Hamburg, Hamburg 20354
Germany

HOME PAGE: http://www.wiso.uni-hamburg.de/professuren/vwl-wachstum-umwelt-und-ressourcen/

Research School of Economics ( email )

Arndt Building 25a
Canberra, Australian Capital Territory 0200
Australia
0261254667 (Phone)

HOME PAGE: http://rse.anu.edu.au/people/people.php?ID=950

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